class_docstr: Computes the forward decoding in a linear-chain CRF.
code: def get_config(self) -> dict:
      config = {
          "transition_params": tf.squeeze(self._transition_params, 0)
          .numpy()
          .tolist()
      }
      base_config = super(CrfDecodeForwardRnnCell, self).get_config()
      return dict(list(base_config.items()) + list(config.items()))
  
imports: import warnings
  import numpy
  import tensorflow
  from tensorflow_addons.rnn.abstract_rnn_cell import AbstractRNNCell
  from tensorflow_addons.utils.types import TensorLike
  from typeguard import typechecked
  from typing import Optional, Tuple
label_desc: Use image node_id 6 for calling the CrfDecodeForwardRnnCell obj's underlying member method code with example usage: obj.get_config() and returns: dict